Millions of people worldwide contribute content to peer production repositories that serve human information needs and provide vital world knowledge to prominent artifcial intelligence systems. Yet, extreme gender participation disparities exist in which men signifcantly outnumber women. A central concern has been that due to self-focus bias , these disparities can lead to corresponding gender content disparities, in which content of interest to men is better represented than content of interest to women. This paper investigates the relationship between participation and content disparities in OpenStreetMap. We replicate fndings that women are dramatically under-represented as OSM contributors, and observe that men and women contribute diferent types of content and do so about diferent places. However, the character of these diferences confound simple narratives about self-focus bias: we fnd that on a proportional basis, men produced a higher proportion of contributions in feminized spaces compared to women, while women produced a higher proportion of contributions in masculinized spaces compared to men. We discuss the implications of these complex results for both theory and practice.